WO2018137300A1

WO2018137300A1 - Method and apparatus for determining quality of physiological signal

Info

Publication number: WO2018137300A1
Application number: PCT/CN2017/086393
Authority: WO
Inventors: 张�杰; 陈文娟; 董辰; 朱萸
Original assignee: 华为技术有限公司
Priority date: 2017-01-25
Filing date: 2017-05-27
Publication date: 2018-08-02
Also published as: CN108633249A; CN108633249B

Abstract

A method and apparatus for determining quality of a physiological signal, relating to the field of wearable devices, capable of providing the accuracy of the result of determining the quality of the physiological signal and reducing the calculated amount in the process of determining the quality of the physiological signal. The specific solution is: S301, collecting physiological signals, the physiological signals being periodic signals or quasi-periodic signals; S302, extracting feature points of the physiological signals, the feature points comprising a feature point for indicating the period of the physiological signals; S303, dividing the period of the physiological signals according to the feature points of the physiological signals; and S304, determining the quality of signals of the i^th period according to the similarity between the signals of the i^th period and a current signal template set, wherein the signal template set comprises N signal templates, the N signal templates are obtained according to the physiological signals prior to the signals of the i^th period, N is greater than or equal to 2, and i is greater than or equal to N. The method and apparatus is used in the process of determining the quality of physiological signals before obtaining human body physiological information according to the physiological signals of human body.

Description

Method and device for judging physiological signal quality

This application claims the priority of the Chinese patent application filed on January 25, 2017 by the Chinese Patent Office, application number 201710061354.0, and the invention titled "Real-time physiological signal quality judgment method and system for extremely low resource consumption", the entire contents of which are The citations are incorporated herein by reference.

Technical field

Embodiments of the present invention relate to the field of wearable devices, and in particular, to a method and device for judging physiological signal quality.

Background technique

In recent years, wearable devices have been gradually applied to physiological monitoring of human bodies because of their non-invasive, simple and flexible characteristics. Wearable devices can provide patients with low-load, non-contact, long-term continuous physiological monitoring, such as monitoring the body's electrocardiogram (ECG), pulse wave (Photoplethsmogram, PPG), breathing, blood pressure and other physiological signals. Among them, the pulse wave is an abbreviation for electrical volume pulse wave tracing information. The current wearable device acquires the physiological signal of the human body through the wearable sensor, and the wearable sensor is easily interfered by noise and motion artifacts, so that the acquired physiological signal and the human physiological information obtained based thereon deviate from the real situation. Therefore, before the physiological signal is obtained using the physiological signal, the signal quality of the physiological signal must be judged. Specifically, it is determined whether the physiological signal is a normal physiological signal or an abnormal physiological signal interfered by noise and motion artifacts.

In the prior art, before determining the acquired physiological signal quality of the human body, such as electrocardiogram, pulse wave, respiration, blood pressure, etc., it is usually necessary to preset a signal template for judging the quality of the physiological signal; and, in the process of acquiring the physiological signal Generally, a large number of feature values of the physiological signal are accurately acquired, that is, a plurality of feature points of the physiological signal are accurately extracted; thus, the physiological signal quality is determined according to the preset signal template and the plurality of accurate feature values.

The problem is that the above-mentioned preset signal template is usually obtained from a large number of offline physiological signals by using a machine learning algorithm or prior knowledge, and the offline physiological signal is deviated from the real-time acquired physiological signal, thereby The accuracy of the physiological signal quality judgment result obtained by the preset signal template needs to be improved. Moreover, since the current wearable sensors are generally relatively simple, some features of the physiological signal, such as the beat pulse peaks, may not be extracted, that is, the above-mentioned large number of accurate feature values may not be obtained; thus, according to the above-mentioned The accuracy of the physiological signal quality judgment result obtained by the accurate eigenvalue needs to be improved, and the calculation amount in the process of judging the physiological signal quality is large.

Summary of the invention

The present application provides a physiological signal quality judgment method and device, which can improve the accuracy of the physiological signal quality judgment result and reduce the calculation amount in the physiological signal quality judgment process.

To achieve the above objectives, the present application adopts the following technical solutions:

In a first aspect, a physiological signal quality judging method is provided. The physiological signal quality judging method comprises: collecting a physiological signal, wherein the physiological signal is a periodic signal or a periodic signal; and extracting a feature point of the physiological signal, the feature point includes a characteristic point of the physiological signal period; dividing the physiological signal according to a characteristic point of the physiological signal; determining a signal quality of the signal of the i-th period according to the similarity between the signal of the i-th period and the current set of signal templates; The signal template set includes N signal templates, and the N signal templates are acquired according to a physiological signal before the signal of the ith period, where N is greater than or equal to 2, and i is greater than N. In general, each of the N signal templates in the current signal template set is a physiological signal of better quality. Therefore, if the similarity between the signal of the i-th cycle and the current set of signal templates is higher, the signal quality of the signal of the i-th cycle is better; the signal of the i-th cycle is between the current signal template set and the current signal template set. The lower the similarity, the worse the signal quality of the signal of the i-th cycle.

It should be noted that, in the physiological signal quality judging method provided by the present application, the current signal template set for judging the physiological signal quality is obtained according to the physiological signal acquired in real time, instead of using a machine learning algorithm or prior knowledge, from a large number. Obtained in the offline physiological signal; thus, the current signal template provided by the present application is more in line with the physiological signal acquired in real time, so that the accuracy of the physiological signal quality judgment result obtained according to the current signal template set is high.

In a possible implementation manner, determining the signal quality of the signal of the i-th cycle can determine whether the signal of the i-th cycle reaches the standard of the normal physiological signal, that is, whether the signal of the i-th cycle is a normal physiological signal or an abnormal physiological signal. Specifically, determining the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the set of signal templates may include: determining a similar result of the signal of the ith period, where the ith period is The similar result of the signal is used to indicate the similarity between the signal of the i-th cycle and the current set of signal templates; if the similar result of the signal of the i-th cycle satisfies the preset similar condition, the signal of the i-th cycle is judged to be normal. The physiological signal, the preset similar condition is preset; if the similar result of the signal of the i-th cycle does not satisfy the preset similar condition, the signal of the i-th cycle is judged to be an abnormal physiological signal.

The similarity between the signal of the ith period and the current set of signal templates may be represented by a similarity parameter between a sample sequence of the signal of the ith period and a correlation coefficient, a mean square error, and the like of the sample sequence of the signal template. For example, in the case where the similar parameter of the signal of the i-th cycle is the correlation coefficient, the similarity parameter of the signal of the i-th cycle is larger, the similarity is higher, and the signal quality is better. The smaller the similarity parameter of the signal of the i-th cycle, the lower the similarity and the worse the signal quality.

In a possible implementation manner, in the case that determining that the similar result of the signal of the ith period is better than the similar result of the at least one signal template of the N signal templates, the method may further include: according to the ith period The signal updates the current set of signal templates. That is, if the signal quality of the signal of the i-th cycle is higher than the signal quality of at least one of the N signal templates in the current signal template set, the above method can replace the signal according to the signal of the i-th cycle. The template updates the current set of signal templates. The similar result of one of the N signal templates is obtained according to the physiological signal before the signal of the i-th cycle.

It should be noted that the current set of signal templates is continuously updated according to physiological signals acquired in real time. Wherein, the signal with relatively poor signal quality is replaced by a signal with a good signal quality period The number template updates the current set of signal templates such that the signal quality of the signal templates in the current set of signal templates is increased in real time. Thus, the accuracy of the physiological signal quality judgment result obtained according to the current real-time updated current signal template set is high.

In a possible implementation manner, since the signal quality of the signal of the ith period is related to the similar result of the signal of the ith period, the current signal template set may be updated according to the similar result of the signal of the ith period. Specifically, the updating the current signal template set according to the signal of the ith period may include: when determining that the similar result of the signal of the ith period is better than the similar result of the at least one signal template of the N signal templates: The i-cycle signal replaces the worst-performing signal template in the current set of signal templates.

Optionally, the above “replace the signal template with the worst result of the current signal template in the current signal template set by using the signal of the ith period” may be replaced by replacing the similar result in the current signal template set with the signal of the ith period. Signal template. Among them, the similar result of the signal template with any similar similar results is worse than the similar result of the signal of the i-th cycle.

In a possible implementation manner, before determining the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the current set of signal templates, the method may further include: according to the ith period The physiological signal before the signal acquires the current set of signal templates.

The current signal template set may be a signal template set that has been updated. For example, the current signal template set may be a signal template set updated according to the signal of the i-1th period. Alternatively, the current set of signal templates may be a set of signal templates that have not been updated.

In a possible implementation, the acquiring the current signal template set according to the physiological signal preceding the signal of the ith period may include: acquiring an initial signal template set according to the signal of the previous N+a periods; and according to the initial signal template set and The physiological signal between the signal of the N+ath cycle to the signal of the ith cycle acquires the current set of signal templates. The initial signal template set is a signal template set that has not been updated.

It should be noted that the N signal templates in the initial signal template set are not necessarily normal physiological signals with good signal quality, but the physiological signal quality determining method may be performed as long as the initial signal template set includes N signal templates. The method may obtain the current signal template set according to the initial signal template set and the physiological signal between the signal of the N+ath period and the signal of the ith period, and may also be based on the signal of the N+a period. The similar result of the signal for each period between the signals of the i-th cycle determines the signal quality of the signal for each period.

In a possible implementation manner, the acquiring the initial signal template set according to the signal of the previous N+a periods may include: determining a similar result of the signal of each period in the signals of the previous N+a periods; a being greater than or equal to An integer of 0, N+a is less than i; wherein the similar result of the signal of one period in the signals of the first N+a periods is divided by the signal of the period and the signal of the previous N+a period except the signal of the period The similarity between the signals of other periods is composed; the signals of the first N periods with the best result of the previous N+a periods are determined as the initial signal template set.

Wherein, when a is equal to 0, the N signal templates in the initial signal template set are the signals of the first N periods. When a is greater than 0, the signals of the first N+a periods have a period of signals that are not the signal templates in the initial signal template set. It should be noted that the above N+a cycles are determined. After the similarity of the signals in each period of the signal, it is also possible to judge the signal quality of the signal of each of the signals of the previous N+a periods.

In a possible implementation manner, the extracting the feature point of the physiological signal may further include: acquiring the feature value of the signal of the i-th cycle according to the feature point of the physiological signal; determining the feature value of the signal of the i-th cycle is not Within the current preset threshold range, and determining that the signal of the i-th cycle is an abnormal physiological signal, the current preset threshold range is determined according to the signal of the period before the signal of the i-th cycle; the signal and signal according to the i-th cycle Before the similarity between the template sets determines the signal quality of the signal of the i-th cycle, the method may further include: determining that the feature value of the signal of the i-th cycle is within a current preset threshold range.

It should be noted that, since the current preset threshold range is obtained according to signals of all periods in the physiological signal acquired in real time, that is, the current preset threshold range is obtained according to a global variable; therefore, the current preset threshold range is consistent with real-time acquisition. Physiological signals. Therefore, the physiological signal quality judging method provided by the present application can further improve the accuracy of the physiological signal quality judgment result.

In a possible implementation manner, in the case that the feature points of the extracted physiological signal include a vertex and a bottom point, the characteristic values of the signal of the i-th period include: a period value of the signal of the i-th period and/or The height value of the signal for the ith cycle. Thus, the current preset threshold range may include: a current preset period range and/or a current preset height range. Specifically, the feature value of the signal of the ith period is not in the current preset threshold range, and the period value of the signal of the ith period is not in the current preset period range, and/or the height of the signal in the ith period. The value is not within the current preset height range. The eigenvalue of the signal of the ith period is in the current preset threshold range. The period value of the signal of the ith period is in the current preset period range, and the height value of the signal of the ith period is in the current preset height range.

It should be noted that the method provided by the present application extracts the vertices and bottom points in the characteristic values of the physiological signals to determine the signal quality of the signals in each period of the physiological signal, and can reduce the process of judging the physiological signal quality to a certain extent. The amount of calculation in .

In a possible implementation, before the acquiring the feature value of the signal of the ith period according to the feature point of the physiological signal, the method may further include: determining, according to the signal of the period before the signal of the ith period, the current And the preset threshold range; after acquiring the feature value of the signal of the ith period according to the feature point of the physiological signal, the method further includes: updating the current preset threshold range according to the feature value of the signal of the ith period.

The current preset threshold range is continuously updated according to the physiological signal acquired in real time; therefore, the current preset threshold range is consistent with the physiological signal acquired in real time. Therefore, the physiological signal quality judging method provided by the present application can further improve the accuracy of the physiological signal quality judgment result.

In a possible implementation, the method may further include: outputting a signal quality judgment result, where the signal of the ith period is a normal physiological signal or the signal of the ith period is an abnormal physiological signal, and The signal of each cycle before the signal of the i-th cycle is a normal physiological signal or the signal of each cycle is an abnormal physiological signal. Wherein, if the similar result of the signal of one period before the signal of the i-th period satisfies the preset similar condition, the signal of the period is positive Normal physiological signal; if the similar result of the signal of one cycle before the signal of the i-th cycle does not satisfy the preset similar condition, the signal of the cycle is an abnormal physiological signal.

It should be noted that the physiological signal quality judging method provided by the present application can determine the signal quality of the collected physiological signals in real time and on a cycle-by-cycle basis, and accurately distinguish whether the signal of any one of the physiological signals is a normal physiological signal or Abnormal physiological signal. In this way, more accurate physiological information of the human body can be obtained according to the normal physiological signals obtained by the judgment. Moreover, the output signal quality judgment result makes the result more intuitively displayed to the user or related technical personnel to improve the user experience or meet the needs of relevant technicians.

In a second aspect, a physiological signal quality judging device is provided, including: an acquisition module, an extraction module, a division module, and a determination module. The acquisition module is configured to collect a physiological signal, and the physiological signal is a periodic signal or a periodic signal. The extraction module is configured to extract feature points of the physiological signals collected by the collected module, and the feature points include feature points for indicating a period of the physiological signal. The dividing module is configured to divide the physiological signal according to a feature point of the physiological signal extracted by the extraction module. a determining module, configured to determine a signal quality of the signal of the i-th period according to the similarity between the signal of the i-th cycle and the current set of signal templates; wherein the signal template set includes N signal templates, and the N signal templates are based The physiological signal before the signal of the i-th cycle acquired by the acquisition module is acquired, N is greater than or equal to 2, and i is greater than N.

In a possible implementation manner, the foregoing apparatus may further include: a determining module. The determining module is configured to determine a similar result of the signal of the i th period divided by the dividing module, and the similar result of the signal of the i th period is used to indicate the similarity between the signal of the i th period and the current set of signal templates Sex. The determining module is specifically configured to determine that the signal of the i-th cycle is a normal physiological signal if the similar result of the signal of the i-th cycle satisfies a preset similar condition, and the preset similar condition is preset; if the i-th cycle If the similar result of the signal does not satisfy the preset similar condition, the signal of the i-th cycle is judged to be an abnormal physiological signal.

In a possible implementation manner, the foregoing apparatus may further include: an update module. The update module is configured to: when determining that the similar result of the signal of the i th period is better than the similar result of the at least one signal template of the N signal templates, update the current signal template set according to the signal of the i th period, where The similarity of one of the N signal templates is obtained based on the physiological signal before the signal of the i-th cycle.

In a possible implementation, the updating module is specifically configured to replace the signal template with the worst result in the current signal template set by using the signal of the ith period.

In a possible implementation manner, the foregoing apparatus may further include: an acquiring module. The obtaining module is configured to: before the determining module determines the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the current set of signal templates, according to the ith period The physiological signal before the signal acquires the current set of signal templates.

In a possible implementation manner, the acquiring module is specifically configured to acquire an initial signal template set according to the signals of the first N+a periods; and according to the initial signal template set and the signal of the N+a period to the ith cycle The physiological signal between the signals acquires the current set of signal templates.

In a possible implementation manner, the foregoing determining module may also be used to determine the first N+a weeks. The similarity of the signals in each period of the period signal; a is an integer greater than or equal to 0, and N+a is less than i; wherein the similar result of the signal of one period in the signals of the first N+a periods is the signal of the period It is composed of the similarity between the signals of the other periods except the signal of the period in the signals of the previous N+a periods. The acquiring module is specifically configured to determine, as the initial signal template set, the signals of the first N periods with the best similar results among the signals of the previous N+a periods determined by the determining module.

In a possible implementation manner, the acquiring module may be further configured to: after the extracting module extracts the feature point of the physiological signal, acquire the feature value of the signal of the ith period according to the feature point of the physiological signal. The determining module may be further configured to determine that the eigenvalue of the signal of the ith period is not within the current preset threshold, and determine that the signal of the ith period is an abnormal physiological signal, and the current preset threshold range is according to the ith period. Determining the signal of the period before the signal; determining the characteristic value of the signal of the i-th period before determining the signal quality of the signal of the i-th period based on the similarity between the signal of the i-th period and the current set of signal templates The current preset threshold range.

In a possible implementation manner, the characteristic value of the signal of the ith period includes: a period value of the signal of the ith period and/or a height value of the signal of the ith period. The current preset threshold range may include: a current preset period range and/or a current preset height range. The feature value of the signal of the ith period is not in the current preset threshold range, and may include: the period value of the signal of the ith period is not in the current preset period range, and/or the height value of the signal of the ith period is not at The current preset height range. The eigenvalue of the signal of the ith period is in the current preset threshold range, and the period value of the signal of the ith period is in the current preset period range, and the height value of the signal of the ith period is in the current preset height range. .

In a possible implementation manner, the determining module may be further configured to: before the obtaining module acquires the feature value of the signal of the ith period according to the feature point of the physiological signal, according to the period before the signal of the ith period The signal determines the current preset threshold range. The update module may be further configured to: after acquiring the feature value of the signal of the i-th cycle according to the feature point of the physiological signal, the update module updates the current preset threshold range according to the feature value of the signal of the i-th cycle.

In a possible implementation manner, the foregoing apparatus may further include: an output module. The output module is configured to output a signal quality judgment result, and the signal quality judgment result comprises: the signal of the i-th cycle obtained by the judgment module is a normal physiological signal or the signal of the i-th cycle is an abnormal physiological signal, and the ith cycle The signal of each cycle before the signal is a normal physiological signal or the signal of each cycle is an abnormal physiological signal. Wherein, if the similar result of the signal of one period before the signal of the i-th period satisfies the preset similar condition, the signal of the period is judged to be a normal physiological signal; if the signal of the period of the period before the signal of the i-th period is similar If the result does not satisfy the preset similar condition, the signal of the period is judged to be an abnormal physiological signal.

In a third aspect, a physiological signal quality judging device can include a processor, a memory, a display, an inputter, and a bus; the memory is configured to store the at least one instruction, the processor, the memory, the The display and the input device are coupled by the bus, and when the device is operative, the processor executes at least one instruction stored in the memory to cause the device to perform physiological signal quality determination as in the first aspect and various alternatives of the first aspect method.

In a fourth aspect, a computer storage medium is provided, wherein at least one of the computer storage medium is stored And when the at least one instruction is run on the computer, causing the computer to perform the physiological signal quality determination method as in the first aspect and the various alternatives of the first aspect.

In a fifth aspect, a computer program is provided, wherein at least one instruction is stored in the computing program product; and when the at least one instruction is run on a computer, causing the computer to perform the various alternatives as in the first aspect and the first aspect The physiological signal quality judgment method.

It should be noted that the processor in the third aspect of the present application may be the integration of the extraction module, the division module, the determination module, the determination module, the update module, and the acquisition module in the second aspect, and the processor may implement the The functions of the above various functional modules. For a detailed description of the various components in the second aspect and the third aspect, and the beneficial effects analysis, reference may be made to the corresponding descriptions and technical effects in the foregoing first aspect and various possible implementation manners, and details are not described herein again.

DRAWINGS

1 is a schematic structural diagram of a wearable device according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of waveforms of a physiological signal according to an embodiment of the present invention; FIG.

FIG. 3 is a schematic flowchart of a method for judging a physiological signal quality according to an embodiment of the present invention;

4 is a schematic diagram of waveforms of another physiological signal according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of waveforms of another physiological signal according to an embodiment of the present invention; FIG.

FIG. 6 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 7 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 8 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 9 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 10 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 11 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 12 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 13 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 14 is a schematic flowchart diagram of another method for judging physiological signal quality according to an embodiment of the present invention;

FIG. 15 is a schematic diagram of a possible composition of a physiological signal quality judging device according to an embodiment of the present invention;

FIG. 16 is a schematic diagram of another possible composition of a physiological signal quality judging device according to an embodiment of the present invention;

FIG. 17 is a schematic diagram of another possible composition of a physiological signal quality judging device according to an embodiment of the present invention;

FIG. 18 is a schematic diagram of another possible composition of a physiological signal quality judging device according to an embodiment of the present invention;

FIG. 19 is a schematic diagram of another possible composition of a physiological signal quality judging device according to an embodiment of the present invention;

FIG. 20 is a schematic diagram of another possible composition of a physiological signal quality judging device according to an embodiment of the present invention.

detailed description

Embodiments of the present invention provide a method and device for judging physiological signal quality, which are applied to a process for obtaining physiological information of a human body according to physiological signals of a human body, and are specifically applied to determine the quality of the physiological signal before obtaining physiological information of the human body according to physiological signals of the human body. In the process, the accuracy of the physiological signal quality judgment result can be improved, and the calculation amount in the physiological signal quality judgment process can be reduced.

The technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings in the embodiments of the present invention.

The physiological signal quality judging method provided by the embodiment of the present invention may be a physiological signal having periodic or periodicity, such as a physiological signal having periodicity such as electrocardiogram, pulse wave, respiration, and blood pressure of the human body. Wherein, the physiological signals all contain a large amount of physiological information of the human body, for example, the pulse wave signal of the human body may include physiological information such as heart rate, respiratory rate and blood oxygen of the human body.

It should be noted that, in addition to determining the signal quality of the physiological signal, the physiological signal quality determining method provided by the embodiment of the present invention can also determine other signal quality with periodic or periodic signals, such as in the step counting algorithm. The acceleration signal is not limited in this embodiment of the present invention.

The physiological signal quality judging device provided by the embodiment of the present invention may be a wearable device capable of acquiring a physiological signal of a human body. Among them, the wearable device is a portable device that is directly worn on the user's body or integrated into the user's clothes or accessories, and most of the wearable devices have an intelligent system built in, which can connect the mobile phone and various terminals. It has one or more of the above functions such as photographing, GPS positioning, family calling, intelligent anti-lost, monitoring sleep, monitoring heart rate, running pace and so on. Common wearable devices include smart wristbands supported by wrists, smart watches and other products, smart shoes, socks or other products worn on the legs supported by the feet, smart glasses, helmets and headbands supported by the head. And other products, as well as intelligent body temperature stickers, heart rate belts, smart clothing, school bags, crutches, accessories and other forms of products.

Illustratively, FIG. 1 is a schematic structural diagram of a wearable device according to an embodiment of the present invention. Referring to FIG. 1, the wearable device 10 may include one or more of the following components: a sensor component 101, a memory 102, and a processing component 103. Multimedia component 104, audio component 105, input/output (I/O) interface 106, power component 107, and communication component 108.

Among other things, sensor assembly 101 includes one or more sensors for providing state assessment of various aspects to wearable device 10. The state change of each aspect provided by the wearable device 10 described above may be caused by an operation of a user who uses the wearable device 10 or caused by a change in physiological information of the user.

Illustratively, the sensor assembly 101 can detect the open/closed state of the wearable device 10, the relative positioning of the components. The sensor assembly 101 can also detect a change in position of the wearable device 10 or one of the components, orientation of the wearable device 10 or acceleration/deceleration, and temperature changes of the wearable device 10. Sensor assembly 101 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Specifically, the sensor component 101 may include a pulse sensor, such as an infrared pulse sensor, a heart rate pulse sensor, a photoelectric pulse sensor, a wrist pulse sensor, or a digital pulse sensor, for detecting a pulse wave of a user, so that a physiological rate such as a heart rate can be obtained. information. Among them, the commonly used pulse sensor can be a PPG sensor. The sensor assembly 101 can include a blood pressure sensor for detecting blood pressure of the human body. In some embodiments, sensor assembly 101 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. For example, the above CMOS or CCD image sensor can be used to acquire a video signal of a bare portion of the skin such as a face or a hand of a human body. The video signal may include multiple frames, each frame is a two-dimensional image, and the two-dimensional image is a red, green, and blue RGB image, and the RGB image may be divided into an R channel image, a G channel image, and a B channel image. Image, these three images can be used to extract the pulse wave signal of the human body. In other embodiments, the sensor assembly 101 can also include an acceleration sensor, a gyro sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The memory 102 is configured to store various types of data to support operation at the wearable device 10. Examples of such data include instructions for any application or method operating on wearable device 10, contact data, phone book data, messages, pictures, videos, and human physiological information. The memory 102 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable. Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), Magnetic Memory, Flash Memory, Disk or Optical Disk.

Processing component 103 typically controls the overall operation of wearable device 10, such as operations associated with displays, phone calls, data communications, camera operations, and recording operations, as well as processing signals or data acquired by sensors. Specifically, after the sensor component 101 detects and acquires the physiological signal, the processing component 103 can determine the quality of the physiological signal, and obtain the physiological signal as a normal physiological signal or the physiological signal is an abnormal physiological signal; thereby, obtaining the human body according to the normal physiological signal. Physiological information. The processing component 103 can include one or more processors 1031 to execute the instructions. Moreover, processing component 103 can include one or more modules to facilitate interaction between component 103 and other components. For example, processing component 103 can include a multimedia module to facilitate interaction between multimedia component 104 and processing component 103.

The multimedia component 104 includes a screen that provides an output interface between the wearable device 10 and the user. In some embodiments, the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor described above may sense not only the boundary of the touch or slide action but also the duration and pressure associated with the touch or slide operation described above. In some embodiments, the multimedia component 104 includes a camera. When the wearable device 10 is in an operation mode, such as a shooting mode or a video mode, the camera can receive external multimedia data. Each camera can be a fixed optical lens system or have focal length and optical zoom capabilities. Of course, the video signal for obtaining the bare part of the skin such as the face and the hand of the human body can be transmitted by the above CMOS or CCD image sensor or the like. In addition to the sensor acquisition, it can also be obtained by the camera in the multimedia component 104, which is not limited by the embodiment of the present invention.

The audio component 105 is configured to output and/or input an audio signal. For example, the audio component 105 includes a microphone (MC) that is configured to receive an external audio signal when the wearable device 10 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may be further stored in memory 102 or transmitted via communication component 108. In some examples, audio component 105 also includes a speaker for outputting an audio signal. Specifically, in the implementation of the present invention, the audio component 105 can be used to output the physiological signal quality judgment result determined by the processing component 103, and output the physiological information of the human body obtained according to the physiological signal, such as the heart rate of the human body is 65 beats/min ( Beats per minute, bpm).

The I/O interface 106 provides an interface between the processing component 102 and the peripheral interface module, which may be a click wheel, a button, or the like. These buttons may include, but are not limited to, a home button, a start button, and a lock button. Specifically, in the implementation of the present invention, the home button in the I/O interface 106 can also be used to instruct the processing component 103 to start processing the physiological signals acquired by the sensor component 101.

Power component 107 provides power to various components of wearable device 10. Power component 107 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for wearable device 10.

The communication component 108 can support wired or wireless communication between the wearable device 10 and other devices such that the wearable device 10 can access a wireless network based on a communication standard, such as WF, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 108 receives broadcast signals or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 108 described above also includes a near field communication (NFC) module to facilitate short range communication. For example, the NFC module can be implemented based on radio frequency identification (RFD) technology, infrared data association (rDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies. Specifically, in this embodiment of the present invention, the communication component 108 can be configured to send the physiological signal quality judgment result determined by the processing component 103 to the other device, or send the physiological information of the human body obtained according to the physiological signal, for example, the heart rate of the human body is 65 bpm.

In an exemplary embodiment, the wearable device may be implemented by one or more application specific integrated circuits (ASCs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), Programming gate array (FPGA), controller, microcontroller, microprocessor or other electronic component implementation.

In an exemplary embodiment, there is also provided a non-transitory computer readable storage medium comprising instructions, such as a memory 102 comprising instructions executable by the processor 103 of the wearable device. For example, the non-transitory computer readable storage medium described above may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device.

It should be noted that the physiological signal judging device provided in the embodiment of the present invention may be a mobile phone, a personal computer (PC), a tablet computer, etc., which can acquire a physiological signal of a human body, in addition to the above-mentioned wearable device. Terminal Equipment. The embodiments of the present invention are exemplified below by using the above-mentioned physiological signal quality judging device as a wearable device as an example to describe the physiological mechanism provided by the embodiment of the present invention. Signal quality judgment method.

Specifically, in the following embodiments of the present invention, the physiological signal quality determination method provided by the embodiment of the present invention is described by taking the physiological signal as the pulse wave signal as an example.

FIG. 2 is a schematic diagram of a waveform of a physiological signal according to an embodiment of the present invention. The waveform of the physiological signal shown in Fig. 2 is a segment of the pulse wave signal in an ideal case. For ideally suited pulse wave signals, the signals for each cycle can have the same characteristics and feature points. For example, the signal of each period in the pulse wave signal includes the characteristics of rising branch, main peak, heavy beat wave, falling branch, and characteristic points such as vertex and bottom point.

Specifically, the variable of the abscissa t(s) in FIG. 2 is time t, the unit of time t is seconds (s); the variable of ordinate A (mv) is amplitude A, and the unit of amplitude A is millivolts. (mv). B ₁ point, B ₂ point, and B ₃ point are three bottom points, and C ₁ point and C ₂ point are two vertices. The waveform between adjacent bottom points can be a one cycle signal. Of course, in addition to the bottom point, the feature points that distinguish the period of the pulse wave signal in FIG. 2 may be other feature points such as vertices. Exemplarily, the waveform between the bottom point B ₁ and the bottom point B _{2 in} FIG. 2 is a one-cycle signal (referred to as signal period 1); the period value of the signal period 1 can be recorded as T ₁ . The waveform between the bottom point B ₂ and the bottom point B ₃ is a signal of another period (referred to as signal period 2); the period value of the signal period 2 can be recorded as T ₂ . In general, the periodic value of the normal pulse wave signal corresponds to a normal range of the human heart rate of 40 bpm to 180 bpm. FIG 2 is a bottom waveform _between point B to point F. ₁ the main wave signal period 1, F ₁ between the point in the end point of the waveform B ₂ stroke cycle of the signal wave a weight of 1.

Wherein, the bottom point B ₁ is the starting point of the signal period 1. The waveform between the bottom point B ₁ and the vertex C ₁ is the main wave rising branch of the signal period 1, the height value thereof can be written as H _1-1 , and the width value can be recorded as T _1-1 . The waveform between the vertices C ₁ to F ₁ is the main wave falling branch of the signal period 1, the height value can be recorded as H _1-2 , and the width value can be recorded as T _1-2 . Waveform between _1:00 to _1:00 F. G signal rising period of the dicrotic wave branching 1, which may be referred to as a height value H _1-3, width values can be written as T _1-3. The peak at point G ₁ is the peak of the beat wave of signal period 1. Waveform between ₂ G ₁ B point to the bottom point of the dicrotic wave signal period 1 drop branch, which may be referred to as a height value H _1-4, width values can be written as T _1-4. B point ₂ is the end point of signal period 1. Wherein, the period value T _{1 of the} signal period 1 is T _1-1 + T _1-2 + T _1-3 + T _1-4 . The main wave rising branch of the signal period 1 from the bottom point B ₁ to the vertex C ₁ may also be referred to as a systolic wave of the signal period 1; the waveform of the vertex C _{1 to the} bottom point B ₂ may also be referred to as a signal period 1 Diastolic wave. Therefore, the height value of the contraction wave of the signal period 1 is H _1-1 , and the height value of the diastolic wave of the signal period 1 can be written as H _1-5 .

Similarly, the characteristics and characteristic points of the signals of other periods in the pulse wave signal (such as the signal period 2) are similar to those of the signal period 1, and will not be further described herein.

In addition, the area of the graph composed of the bottom point B ₂ to E _{2 of the} signal period 2 and the coordinate axis t(s) can be written as S _a ; the waveform between the E ₂ point and the bottom point B ₃ and the coordinate axis t ( s) The area of the composed graph can be written as S _b ; the area of the graph composed of the signal period 2 and the coordinate axis t(s) can be written as S, that is, the waveform between the bottom point B _{2 and the} bottom point B ₃ The area of the graph composed of the coordinate axis t(s) can be written as S. Where S = S _a + S _b . Similarly, for the description of the signal period 1 of the pulse wave signal or the waveform of the signal period and the area of the graph composed of the coordinate axes, reference may be made to the above description of the signal period 2, and details are not described herein again.

It should be noted that since the current wearable sensor is relatively simple and most of the wrist signals are acquired, the pulse wave signals acquired by the current wearable sensors often do not see features such as heavy beat waves and the peaks of the beat pulses. Feature point. However, current wearable sensors generally have the bottom and apex of the pulse wave signal. Similarly, current wearable sensors can generally acquire vertices and bottom points of physiological signals other than pulse wave signals, and are not described here. In the following embodiments of the present invention, the physiological signal quality judging method provided by the embodiment of the present invention is described by taking the feature points of the physiological signal as the vertices and the bottom point as an example.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the physiological signals provided by the embodiments of the present invention are provided by the flowchart of the physiological signal quality judging method shown in FIG. 3 in conjunction with the wearable device 10 shown in FIG. The quality judgment method is described in detail. Referring to FIG. 3, the physiological signal quality determining method provided by the embodiment of the present invention may include S301-S304:

S301. The wearable device collects a physiological signal, where the physiological signal is a periodic signal or a periodic signal.

The step 301 can be performed by the sensor component 101 in the wearable device 10 shown in FIG. 1, such as a PPG sensor.

Illustratively, the sensor component 101 can collect physiological signals at a fixed sampling frequency for a fixed duration (eg, 3 s), and the acquired physiological signals are a set of discrete samples.

The sampling frequency does not affect the implementation of the purpose of the present application. The sampling frequency is not specifically limited in the embodiment of the present invention, for example, may be 25-100 Hz.

It should be noted that after the physiological signal is acquired by the wearable device, the physiological signal may be preprocessed, such as filtering, to acquire a pulse wave signal, as shown in FIG. 4 , which is a preprocessed pulse wave signal. The pre-processing process may be performed by a processor in the wearable device, or may be performed by a separate filtering component in the wearable device. The filtering component may be a hardware-implemented filter, which is not limited by the embodiment of the present invention.

S302. The wearable device extracts a feature point of the physiological signal, where the feature point includes a feature point for indicating the period of the physiological signal.

Wherein, the feature point for indicating the period of the physiological signal may be a vertex and a bottom point of the physiological signal.

Optionally, the feature point may also be a feature point other than a bottom point and a vertex in the physiological signal, such as a feature point where a beat wave peak of the pulse wave signal is located.

In the physiological signal (such as pulse wave physiological signal) extracted by the above wearable device, the waveform between adjacent bottom points may be one cycle, or the waveform between adjacent vertices may be one cycle; and the wearable device is The signal quality of the physiological signal is determined on a cycle-by-cycle basis. Therefore, the method provided by the embodiment of the present invention may further include S303:

S303. The wearable device divides the physiological signal according to a feature point of the physiological signal.

Illustratively, as shown in FIG. 5, it is a waveform diagram of a physiological signal provided by an embodiment of the present invention. Figure 5 shows the bottom point and apex of the wearable device extracted by the wearable sensor for the pulse wave signal shown in Figure 4. Subsequently, the wearable device can divide the waveforms between adjacent bottom points as in Fig. 5, and record the signals of each period in chronological order, that is, record the sequence of samples of the signals of each period.

Wherein the wearable device to obtain a signal sample sequence of the first cycle may be recorded as _{_{x 1 = {x 1_1, x}} 1_2, ... x 1_j, ..., x 1_n}, j∈ {1,2, ......, n }, the sample sequence x ₁ of the signal of the 1st cycle may include n samples, n being a positive integer; x _{1_j} is the jth sample in the sample sequence x ₁ of the signal of the 1st cycle. Similarly, when the wearable device acquires the signal of any period after the signal of the first period, the sample sequence of the signal of the period may also be recorded, and the sample sequence of the signal of the period may also include n samples.

It should be noted that, when the sampling frequency provided in the embodiment of the present invention is 100 Hz, the time interval between two samples in the sample sequence of the signal of each period acquired by the wearable device may be 0.01 s. 3 and FIG. 5, the time T ₁ of the signal of the first period shown in FIG. 5 may be 0.3 s, and the waveform of the signal of the first period may include 30 points. That is, 30 samples may be included in the sample sequence of the signal of the first period.

S304. The wearable device determines a signal quality of the signal of the i-th period according to the similarity between the signal of the i-th cycle and the current set of signal templates.

The above steps 302-304 can all be performed by the processing component 102 in the wearable device 10 shown in FIG. 1.

The current set of signal templates includes N signal templates, and the N signal templates can be acquired according to physiological signals preceding the signal of the i-th cycle, where N is greater than or equal to 2, and i is greater than N. That is to say, the above N signal templates may be N signals of the signals of the first period to the signals of the i-1th period, and the N signal templates are acquired by the wearable device in real time. The similarity between the signal of the ith cycle and the current set of signal templates is composed of the similarity between the signal of the ith cycle and each of the N signal templates included in the current set of signal templates.

There is a similarity between the signals of every two cycles in the signal of the period acquired by the wearable device. The similarity between the signals of these two periods can be used to indicate the degree of similarity of the waveforms of the signals of the two periods. For example, the higher the similarity between the signals of the two periods, the higher the degree of similarity of the waveforms of the signals representing the two periods; the lower the similarity between the signals of the two periods, the signals representing the two periods The lower the similarity of the waveform. That is, the higher the similarity between the signal of the ith period and any of the signal templates, the higher the degree of similarity between the waveform of the signal of the ith period and the waveform of the signal template; and further, the ith period The similarity between the signal and the current set of signal templates is higher. The lower the similarity between the signal of the ith period and any of the signal templates, the lower the degree of similarity between the waveform of the signal of the ith period and the waveform of the signal template; further, the signal of the ith period and the current The similarity between the sets of signal templates is lower.

In general, each of the N signal templates in the current signal template set is a physiological signal of better quality. Therefore, if the similarity between the signal of the i-th cycle and the current set of signal templates is higher, the signal quality of the signal of the i-th cycle is better; the signal of the i-th cycle is between the current signal template set and the current signal template set. The lower the similarity, the worse the signal quality of the signal of the i-th cycle.

The wearable device can record the sample sequence of the signal of the ith period while acquiring the signal of the ith period, for example, the signal sample sequence of the ith period can be recorded as x _i ={x _{i_1} , x _{i_2} ,... x _{i_j} ,...,x _{i_n} },j∈{1,2,...,n}. At this time, the signal of the i-th cycle may also be simply referred to as x _i . Wherein, the sample sequence x _i of the signal of the i-th cycle includes n samples, and x _{i_j} is the j-th sample in the sample sequence x _i of the signal of the i-th cycle. Of course, the wearable device may have recorded a sample sequence of signals for each of the first i-1 cycles of the signal before the wearable device acquires the signal for the ith cycle. For example, the wearable device may sample sequence recorded signal in the i-1 cycles as _{_{x i-1 = {x i}} -1_1, x i-1_2, ... x i-1_j, ..., x i-1_n}, The sample sequence x _i-1 of the signal of the _i-1th period may also include n samples, and x _{i-1_j} is the jth sample in the sample sequence x _i-1 of the signal of the _i-1th period.

It should be noted that, in the physiological signal quality determining method provided by the embodiment of the present invention, the current signal template set for determining the physiological signal quality is obtained by the wearable device according to the physiological signal acquired in real time, instead of using a machine learning algorithm or Obtaining knowledge, obtained from a large number of offline physiological signals; thus, the current signal template provided by the embodiment of the present invention more closely matches the physiological signal acquired by the wearable device in real time, so that the physiological signal quality judgment result obtained according to the current signal template set is High accuracy. Moreover, since the wearable device extracts the vertices and the bottom point in the physiological signal after obtaining the physiological signal, the wearable device can support the wearable device to determine the physiological signal quality, and does not necessarily need to extract the vertices and the bottom point in the physiological signal. There are a large number of other feature points to support the wearable device to judge the physiological signal quality; therefore, the amount of calculation in the process of determining the physiological signal quality of the wearable device can be reduced, and the accuracy of the physiological signal quality judgment result can be further improved.

Specifically, in a possible implementation, the wearable device determines the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the current set of signal templates, and can determine the ith period. Whether the signal is a normal physiological signal or an abnormal physiological signal. S304 in the physiological signal quality determining method provided by the embodiment of the present invention may include S601-S603 or S601, S602, and S604. Illustratively, as shown in FIG. 6 , it is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. In FIG. 6, S304 shown in FIG. 3 may include S601-S603 or S601, S602, S604:

S601. The wearable device determines a similar result of the signal of the i th period, where the similarity result of the signal of the i th period is used to indicate the similarity between the signal of the i th period and the current set of signal templates.

The similarity between the signals of every two cycles in the periodic signal acquired by the wearable device may be represented by a similar coefficient such as a correlation coefficient or a mean square error of the sample sequence of the signals of the two cycles. That is to say, the similarity between the signal of the i-th cycle and the current set of signal templates may be similar parameters such as the correlation coefficient of the sample sequence of the signal of the i-th cycle and the sample sequence of a signal template, the mean square error, and the like. composition. Thus, the similarity between the signal of the ith cycle and the current set of signal templates can be represented by similar parameters of the signal of the ith cycle. Thus, the similar result of the signal of the ith cycle described above may be a similar parameter of the signal of the ith cycle. The similar parameter of the signal of the ith period may be the sum of the signal of the ith period and the similar parameter of each of the current N signal templates, or the signal of the ith period and the current N signals. The mean between similar parameters for each signal template in the template.

Wherein, the wearable device can record the current signal template set as y={y ₁ , y ₂ , . . . y _t , . . . , y _N-1 , y _N }, t ∈ {1, 2, . . . , N}, The y _t is a sample sequence of the tth signal template in the current N signal templates. At the same time, the wearable device can record the sample sequence y _{t of} the tth signal template as y _t ={y _{t_1} , y _{t_2} ,...y _{t_j} ,...,y _{t_n} },j∈{1,2,...,n }. The sample sequence y _t of the t-th signal template may also include n samples, and y _{t_j} is the j-th sample in the sample sequence y _t of the t-th signal template. Subsequently, the wearable device can record the signal of the i-th cycle and the similar parameter of the t-th signal template of the current N signal templates as r _{i_t} . Thus, the similarity parameter r _{i_t} of the signal of the i-th cycle can be recorded as:

or,

It should be noted that any one of the current signal template sets y is a one-cycle signal. For example, the first signal template y ₁ may be the signal x _{1 of the} first period. For convenience of description, a signal template and periodic signals corresponding to the signal template are respectively represented by different characters.

Illustratively, where the similarity between two cycles of signals is represented by the correlation coefficients of the sample sequences of the signals of the two cycles: the signal of the ith cycle and the tth signal of the current N signal templates The similarity parameter r _{i_t} of the template is the correlation coefficient between the sample sequence x _i of the signal of the i-th cycle and the sample sequence y _t of the t-th signal template of the current N signal templates.

Specifically, the similar parameter r _{i_t} of the signal of the i th period and the t signal template of the current N signal templates may be:

among them,

Is the mean of n samples in the sample sequence x _i of the signal of the ith cycle, and

Is the mean of n samples in the sample sequence y _t of the t-th signal template, and

Further, will

In the equation (1), the similar parameter r _{i_t} of the signal of the i-th period and the t-th signal template of the current N signal templates may also be:

It should be noted that if the correlation coefficient of the sample sequence of the signals of two periods is larger, the similarity between the signals of the two periods is higher; otherwise, the similarity between the signals of the two periods is lower. . Therefore, if the similarity parameter r _{i_t} is larger, the similarity between the signal of the i-th cycle and the t-th signal template of the current N signal templates is higher; and further, the i-th cycle obtained according to the similar parameter r _{i_t} The larger the similarity parameter r _i of the signal, the better the similar result of the signal of the i-th cycle, and the better the signal quality of the signal of the i-th cycle. If the similarity parameter r _{i_t is} smaller, the similarity between the signal of the i-th cycle and the t-th signal template of the current N signal templates is lower; and further, the signal of the i-th cycle obtained according to the similar parameter r _{i_t} The smaller the similarity parameter r _{i is} , the worse the similar result of the signal of the i-th cycle is, and the worse the signal quality of the signal of the i-th cycle is.

In another example, the similarity between the signals of the two cycles is represented by the mean square error of the sample sequence of the signals of the two cycles: the signal of the ith cycle and the current N signal templates The similarity parameter r _{i_t} of the t-th signal template is the mean square error of the sample sequence x _i of the signal of the i-th cycle and the sample sequence y _t of the t-th signal template of the current N signal templates.

Specifically, the mean square error mse _{i_t} (ie, the similar parameter r _{i_t} ) of the signal of the i-th period and the t-th signal template of the current N signal templates may be:

Where a _{i_j} is the j-th sample of the sample sequence a _i obtained by normalizing the sample sequence x _i of the signal of the i-th cycle, and the sample sequence y _t of the t-th signal template obtained by b _{i_j} is normalized The j-th sample of the sample sequence b _t .

Wherein, the difference from the correlation coefficient is that if the mean square error of the sample sequence of the signals of the two periods is smaller, the similarity between the signals of the two periods is higher; otherwise, between the signals of the two periods The lower the similarity. Therefore, in the case where the similarity parameter r _{i_t} is the mean square error mse _{i_t} , if the similarity parameter r _{i_t is} smaller, the similarity between the signal of the i-th cycle and the t-th signal template of the current N signal templates is Higher; further, the smaller the similarity parameter r _i of the signal of the i-th cycle obtained according to the similar parameter r _{i_t} is, the better the similar result of the signal of the i-th cycle is, and the better the signal quality of the signal of the i-th cycle is. . If the similarity parameter r _{i_t} is larger, the similarity between the signal of the i-th cycle and the t-th signal template of the current N signal templates is lower; and further, the signal of the i-th cycle obtained according to the similar parameter r _{i_t} The larger the similarity parameter r _i is, the worse the similar result of the signal of the i-th cycle is, and the worse the signal quality of the signal of the i-th cycle is.

It should be noted that, in the embodiment of the present invention, the similarity between the signals of the two periods is represented by the correlation coefficient of the sequence of the signal samples of the two periods, and the method for judging the physiological signal quality provided by the embodiment of the present invention is described.

Further, the wearable device determines the signal quality of the signal of the ith period according to the similar result of the signal of the ith period, and specifically, the wearable device determines whether the signal of the ith period is a normal physiological signal or an abnormal physiological signal.

S602. The wearable device determines whether the similar result of the signal of the i-th cycle satisfies a preset similar condition.

The preset similar condition may be preset by the wearable device before executing S602. The preset similar condition may be used to indicate whether the signal of each period in the physiological signal acquired by the wearable device is a normal physiological signal.

It should be noted that when the similarity between the signals of the two periods is represented by the correlation coefficient of the sample sequence of the signals of the two periods, the similar parameters of the signals of the two periods may have a value range of [0, 1]. In general, if the similarity parameter of the signal of two periods is greater than or equal to 0.8, it indicates that the similarity between the signals of the two periods is higher; if the similarity parameter of the signal of the two periods is less than 0.8, then The similarity between the signals of these two periods is low. If the similarity parameter of the two-cycle signal is equal to 0, then there is no similarity between the signals of the two cycles. If the similarity parameter of the two-cycle signal is equal to 1, it means that the signals of the two cycles are completely similar.

Wherein, if the similar parameter of the signal of the ith period is the sum of the signal of the ith period and the similarity parameter of each of the current N signal templates, whether the phase result of the signal of the ith period is The similar condition satisfying the preset" may be whether the similar parameter of the signal of the i-th cycle is greater than or equal to 0.8×N. If the similarity parameter of the signal of the i-th cycle is the mean between the signal of the i-th cycle and the similarity parameter of each of the current N signal templates, is the similar result of the signal of the "i-th cycle" The similar condition satisfying the preset" may be whether the similar parameter of the signal of the i-th cycle is greater than or equal to 0.8.

S603. If the similar result of the signal of the i-th cycle satisfies a preset similar condition, the wearable device determines that the signal of the i-th cycle is a normal physiological signal.

Wherein, if the similar result of the signal of the i-th cycle satisfies the preset similar condition, the signal quality of the signal of the i-th cycle reaches the standard of the normal physiological signal, that is, the signal of the i-th cycle is a normal physiological signal. Subsequently, the wearable device can mark the signal of the i-th cycle as a normal physiological signal, and obtain human physiological information according to the signal of the i-th cycle.

S604. If the similar result of the signal of the i-th cycle does not satisfy the preset similar condition, the wearable device determines that the signal of the i-th cycle is an abnormal physiological signal.

Wherein, if the similar result of the signal of the i-th period does not satisfy the preset similar condition, it indicates that the signal quality of the signal of the i-th period does not reach the standard of the normal physiological signal, that is, the signal of the i-th period is an abnormal physiological signal. . Subsequently, the wearable device can mark the signal of the i-th cycle as an abnormal physiological signal, and does not use the signal of the i-th cycle in determining the physiological information of the human body.

Further, in a case where the wearable device determines that the similar result of the signal of the i-th cycle is better than the similar result of the at least one signal template of the current N signal templates, the wearable device can update the current set of signal templates. The above method may further include S701 after the above S603 or S604. Illustratively, as shown in FIG. 7, is a schematic flowchart of another physiological signal quality judging method provided by an embodiment of the present invention. In FIG. 7, after S603 shown in FIG. 6, the above method may further include S701:

S701. The wearable device updates the current signal template set according to the signal of the ith cycle.

The above step 701 can be performed by the processing component 102 in the wearable device 10 shown in FIG.

Wherein, if the signal quality of the signal of the i-th cycle is higher than the signal quality of at least one of the N signal templates in the current signal template set, the wearable device can update the current signal according to the signal of the i-th cycle. Template collection.

It should be noted that the current set of signal templates is continuously updated by the wearable device according to the physiological signals acquired in real time. The signal quality of the signal template in the current signal template set is improved in real time because the wearable device updates the current signal template set according to the signal with a relatively good signal quality and replaces the signal template with relatively poor signal quality. Thus, the accuracy of the physiological signal quality judgment result obtained according to the current real-time updated current signal template set is high.

Generally, the signal for updating one cycle of the current signal template set is a normal physiological signal with better signal quality; of course, it may also be an abnormal physiological signal with better signal quality. Among them, the update of the current signal template by the abnormal physiological signal usually occurs during several update processes after the wearable device obtains the unupdated signal template set.

Since the signal quality of the signal of the ith period in the embodiment of the present invention is related to the similar result of the signal of the ith period, the wearable device can update the current set of signal templates according to the similar result of the signal of the ith period. In another possible implementation manner, in the method for judging the physiological signal quality provided by the embodiment of the present invention, the foregoing S701 may specifically include S801-S802. Illustratively, as shown in FIG. 8 , it is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. In FIG. 8, S701 in FIG. 7 may specifically include S801-S802:

S801. The wearable device determines that the similar result of the signal of the i-th cycle is better than the similar result of the at least one signal template of the current N signal templates.

At this time, the signal quality of the signal of the i-th cycle is higher than the signal quality of at least one of the current N signal templates.

S802. The wearable device replaces the signal template with the worst result in the current signal template set by using the signal of the ith period.

The wearable device replaces the signal template with the worst result in the current signal template set by using the signal of the ith period, so that the wearable device removes the signal template with the worst result from the current signal template set, and uses similar The resulting ith cycle of the signal updates the current set of signal templates as a new signal template. A similar result of one of the N signal templates in the current set of signal templates can be derived from the physiological signal preceding the signal of the ith cycle.

Optionally, the above “the wearable device replaces the worst-case signal template in the current signal template set by using the signal of the ith cycle” may be replaced by the wearable device replacing the current signal template set with the signal of the ith cycle. A signal template with a similarly poor result. Among them, the similar result of the signal template with any similar similar results is worse than the similar result of the signal of the i-th cycle.

It should be noted that the wearable device may also acquire the current signal template before determining the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the current set of signal templates. Specifically, in another possible implementation manner, the method for judging the physiological signal quality provided by the embodiment of the present invention may further include S901 before the foregoing S304 or S601. Illustratively, as shown in FIG. 9, is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. In FIG. 9, before S601 shown in FIG. 8, S901 may be further included:

S901. The wearable device acquires a current signal template set according to a physiological signal before the signal of the i-th cycle.

The above step 901 can be performed by the processing component 102 in the wearable device 10 shown in FIG.

The current set of signal templates may be a set of signal templates that have been updated by the wearable device. For example, the current set of signal templates may be a set of signal templates that have been updated by the wearable device according to the signal of the i-1th cycle. Alternatively, the current set of signal templates may be a set of signal templates that are not updated by the wearable device, and the current set of signal templates is a set of initial signal templates acquired by the wearable device.

Specifically, in another possible implementation manner, the wearable device may further acquire an initial signal template set that has not been updated before acquiring the current signal template set according to the physiological signal before the signal of the ith period. Illustratively, as shown in FIG. 10, it is a schematic flowchart of another physiological signal quality judging method provided by an embodiment of the present invention. In FIG. 10, the method shown in FIG. 9 may further include S1001 before S901:

S1001: The wearable device acquires an initial signal template set according to a signal of a previous N+a period.

The above step 1001 can be performed by the processing component 102 in the wearable device 10 shown in FIG.

Wherein, the above N+a is less than i, such as N+a is less than or equal to i-1. The above a is an integer greater than or equal to zero.

Specifically, the wearable device acquires the initial signal template set according to the signals of the previous N+a periods, which may be obtained according to the similarity of the signals of each period in the signals of the previous N+a periods. Therefore, in another possible implementation manner, S1001 in the foregoing method may specifically include S1101-S1102. Illustratively, as shown in FIG. 11, is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. In FIG. 11, S1001 in the method shown in FIG. 10 may specifically include S1101-S1102:

S1101. The wearable device determines the similarity of signals in each of the signals of the previous N+a periods.

The similar result of the signal of one cycle of the signals of the preceding N+a periods is the similarity between the signal of the period and the signals of the period other than the signal of the previous N+a period. Sexual composition. The similarity between the signals of the two periods in the signals of the first N+a periods may also be represented by similar parameters of the signals of the two periods, and the similar parameters may also be samples of the signals of the two periods. The correlation coefficient between the sequences. Thus, a similar result of a signal of one cycle in the signals of the first N+a cycles can be represented by similar parameters of the signals of the cycle.

Referring to the above embodiment, the wearable device can also record a sample sequence of signals for each of the first N+a cycles of the signal. For example, the wearable device can record the signal of the second period as x ₂ ={x _{2_1} , x _{2_2} ,...x _{2_j} ,...,x _{2_n} },j∈{1,2,...,n}; signal recording 3 cycles is _{_{x 3 = {x 3_1, x}} 3_2, ... x 3_j, ..., x 3_n}; recording a signal of N + a-1 cycles to _{x N + a-1 = {} x N _{+a-1_1} , x _{N+a-1_2} ,...x _{N+a-1_j} ,...,x _{N+a-1_n} }; record the signal of the N+ _ath cycle as x _N+a ={x _{N+ A_1} , x _{N+a_2} ,...x _{N+a_j} ,...,x _{N+a_n} }.

Illustratively, a similar result of the signal of the first period acquired by the wearable device is taken as an example to illustrate the similar result of the signal of one period in the signal of the previous N+a period: the similar result of the signal of the first period Can be represented by similar parameters of the signal of the 1st cycle. The wearable device can record the similarity parameter of the signal of the first cycle as r ₁ .

At the same time, the wearable device can record the similar parameters of the signal of the first period and the signal of the second period as r _{1_2} , and the similar parameter r _{1_2} can be the sample sequence x ₁ and the second period of the signal of the first period. The correlation coefficient of the sample sequence x ₂ of the signal. The wearable device can record the similar parameters of the signal of the first period and the signal of the third period as r _{1_3} , and the similar parameter r _{1_3} can be the sample sequence of the signal of the first period x ₁ and the signal of the third period The correlation coefficient of the sample sequence x ₃ . The wearable device can record the similar parameters of the signal of the first period and the signal of the N+a- _1th period as r _{1_N+a-1} , and the similar parameter r _{1_N+a-1} can be the signal of the first period. The correlation coefficient between the sample sequence x ₁ and the sample sequence x N+a-1 of the signal of the _N+a- 1th period. The wearable device may record the similar parameter of the signal of the first period and the signal of the N+a period as r _{1_N+a} , and the similar parameter r _{1_N+a} may be the sample sequence x ₁ of the signal of the first period and Correlation coefficient of the sample sequence x _N+a of the signal of the N+ath cycle.

Therefore, in the case where a is equal to 1, the similarity parameter r ₁ of the signal of the first period may be other than the signal of the first period and the signal of the first period of the signal of the first period and the first period of the previous period. The sum of the similar parameters of the signals of other periods; or the similar parameters of the signals of the first period may be other than the signals of the first period and the signals of the first period of the signals of the first period and the first period of the first period The mean between similar parameters of the signals of other cycles. That is, the similar parameter of the signal of the first cycle may be

r ₁ =r _{1_2} +r _{1_3} +...+r _{1_N} +r _{1_N+1} , or,

In the case where a is not equal to 1, the similar parameter of the signal of the first period may be the period of the signal of the first period and the period of the signal of the first N+a period other than the signal of the first period. The mean between similar parameters of the signal. That is, the similar parameter of the signal of the first cycle may be

Exemplarily, the similar parameter r _{1_2} of the signal of the first period and the signal of the second period may be

among them,

The mean of n samples in the sample sequence x ₁ of the signal for the first period, and

The mean of n samples in the sample sequence x ₂ of the signal for the 2nd cycle, and

Further, will

In the equation (3), the similar parameter r _{1_2} of the signal of the first period and the signal of the second period may also be:

Similarly, the similarity parameter r signal of the first cycle _{1_3,} similar parameters r 1_N _{+ a-1,} similar to the parameter _r 1_N ₊ detailed description of _a and other similar parameters may be reference to the detailed description of the similar parameter r _{1_2} of the present The embodiments of the invention are not described again.

It should be noted that after the wearable device determines the similar result of the signal of each period in the signals of the previous N+a periods, that is, after obtaining the similar parameters of the signals of each period in the signals of the previous N+a periods, It is possible to judge the signal quality of the signal of each of the signals of the previous N+a periods. Specifically, for each of the signals in the first N+a period of the signal: if the similar result of the periodic signal satisfies the preset similar condition, the wearable device determines that the signal of the period is a normal physiological signal; The similar result of the signal does not satisfy the preset similar condition, and the wearable device judges that the signal of the cycle is an abnormal physiological signal.

Further, the wearable device can obtain the initial signal template including the N signal templates from the signals of the previous N+a periods while determining the signal quality of the signal of each period in the signals of the previous N+a periods. set. Specifically, in another possible implementation manner, after the step S1101, the foregoing method further includes S1102:

S1102. The wearable device determines, as the initial signal template set, a signal of a first N period of the best result of the previous N+a periods of the signal.

The above step 1102 can be performed by the processing component 102 in the wearable device 10 shown in FIG.

Wherein, when a is equal to 0, the N signal templates in the initial signal template set are signals of the first N cycles acquired by the wearable device. When a is greater than 0, the signal of the first N+a periods acquired by the wearable device has a signal of a period is not the signal template in the initial signal template set.

It should be noted that after the wearable device acquires the initial signal template set according to the signals of the previous N+a periods, the current signal template set may also be determined when receiving the signal of each period after the signal of the N+a period. . The current signal template set may be an initial signal template set that has not been updated by the wearable device, or the current signal template set may be a signal template set obtained after the wearable device updates the initial signal template set.

Correspondingly, in another possible implementation manner, in the method shown in FIG. 10 or FIG. 11, S901 can be replaced by S1002:

S1002, the wearable device according to the initial signal template set and the signal of the N+a period to the ith The physiological signal between the signals of the cycles acquires the current set of signal templates.

Correspondingly, the above step 1002 can also be performed by the processing component 102 in the wearable device 10 shown in FIG. 1.

Specifically, in a case where N+a is equal to i-1, the current signal template set when the wearable device acquires the signal of the i th period is the initial signal template set that is not updated by the wearable device.

When the N+a is smaller than i-1, when the wearable device acquires the signal of the ith period, the current signal template set is the initial signal template set that is not updated by the wearable device; or the current signal template set is The wearable device updates the set of signal templates obtained by the initial signal template set according to the physiological signal between the signal of the N+ath period and the signal of the ith period.

Illustratively, if N+a is less than i-1, if i-1 is equal to N+a+1, and the similar result of the signal of the i-1th cycle is better than the N included by the initial signal template set. Similar results of at least one signal template in the signal template, the wearable device replaces the signal template with the worst result in the initial signal template set in the initial signal template set using the signal of the i-1th cycle. Then, when the wearable device acquires the signal of the ith period, the current signal template set is a signal template set obtained by replacing the signal template with the worst result in the initial signal template set by using the signal of the i-1th period.

Optionally, the above “the wearable device replaces the worst-case signal template in the initial signal template set by using the signal of the i-1th period” may be replaced by the wearable device replacing the foregoing by using the signal of the i-1th period. Any signal template with a similarly poor result in the initial set of signal templates. Among them, the similar result of the signal template with any similar similar results is worse than the similar result of the signal of the i-1th period.

For example, in the case where N is equal to 5, a is equal to 1, and i-1 is equal to 7, and i is equal to 8, the wearable device acquires the initial set of signal templates from the signals of the first 6 cycles. Suppose that the similar parameter r ₁ of the signal of the first period is equal to 0.7, the similar parameter r ₂ of the signal of the second period is equal to 0.75, and the similar parameter r ₃ of the signal of the third period is equal to 0.8, the signal of the fourth period The similarity parameter r ₄ is equal to 0.85, the similarity parameter r ₅ of the signal of the 5th cycle is equal to 0.85, and the similarity parameter r ₆ of the signal of the 6th cycle is equal to 0.9. At this time, the five signal templates in the initial signal template set acquired by the wearable device may be the signal of the second period, the signal of the third period, the signal of the fourth period, the signal of the fifth period, and the first 6 cycles of the signal. The wearable device can record the initial set of signal templates as y={x ₂ , x ₃ , x ₄ , x ₅ , x ₆ }.

Subsequently, if the similar parameter r ₇ of the signal of the 7th cycle is equal to 0.6, the wearable device does not update the initial set of signal templates. Therefore, when the wearable device acquires the signal of the 8th cycle, the current signal template set is the initial signal template set. That is to say, the five signal templates included in the current signal template set are still signals of the second to sixth periods; the wearable device can record the current signal template set as y={x ₂ , x ₃ , x ₄ , x ₅ , x ₆ }.

If the similar parameter r ₇ of the signal of the 7th cycle is equal to 0.95, the wearable device replaces the signal of the second cycle with the worst result in the initial signal template set by using the signal of the 7th cycle. Therefore, when the wearable device acquires the signal of the 8th cycle, the current signal template set is a signal template set obtained by updating the initial signal template set. That is to say, the five signal templates included in the current signal template set are signals of the 2-7th cycle; the wearable device can record the current signal template set as y={x ₇ , x ₃ , x ₄ , x ₅ , x ₆ }.

The N signal templates in the initial signal template set obtained by the wearable device are not necessarily normal physiological signals with good signal quality, but the initial signal template set includes N signal templates to support the wearable device to perform the present invention. The physiological signal quality judging method provided by the embodiment. As the number of cycles in the physiological signal acquired by the wearable device increases, the current set of signal templates can be continuously updated so that the signal quality of any of the current signal template sets can be improved. That is, the N signal templates in the current signal template set updated by the wearable device are generally normal physiological signals with good signal quality. Thereby, the accuracy of the physiological signal quality judgment result obtained by the wearable device according to the current signal template set is high.

It should be noted that, when the wearable device acquires the current signal template set according to the initial signal template set and the signal of the period between the signal of the N+ath period and the signal of the ith period, the N+a may also be determined. A similar result of the signal of each period between the signals of the period to the signal of the ith period. The wearable device can obtain a similar parameter of the signal of each period between the signal of the N+ath period and the signal of the ith period to determine the signal of the N+ath period to the signal of the ith period. The signal quality of the signal between each cycle. Specifically, the signal of each period between the signal of the N+ath period and the signal of the ith period: if the similar result of the periodic signal satisfies a preset similar condition, the wearable device determines the signal of the period It is a normal physiological signal; if the similar result of the periodic signal does not satisfy the preset similar condition, the wearable device judges that the signal of the cycle is an abnormal physiological signal.

Further, the signals of each period in the physiological signals acquired by the wearable device may have the same feature points. Therefore, the wearable device can also determine the signal quality of the physiological signal according to the feature value corresponding to the feature point of the physiological signal. Specifically, in another possible implementation manner, in the physiological signal quality determining method provided by the embodiment of the present invention, the foregoing S303 may further include S1201, S1202, and S1203. Illustratively, as shown in FIG. 12, it is a schematic flowchart of another physiological signal quality judging method provided by an embodiment of the present invention. In FIG. 12, S1201 in FIG. 3 may further include S1201, S1202, and S1203:

S1201: The wearable device acquires the feature value of the signal of the i-th cycle according to the feature point of the physiological signal.

Wherein, the wearable device can acquire the period value of the signal of each period and the height value of the signal of each period according to the vertices and the bottom point of the signal of each period in the physiological signal. Therefore, the characteristic value of the signal of the i-th period includes the period value of the signal of the i-th period and/or the height value of the signal of the ith period. The height value of the signal of the ith period may include a left branch height value of the signal of the ith period and a right branch height value of the signal of the ith period. Specifically, the period value of the signal of each period may be a time interval between two adjacent bottom points in the signal of the period; the height value of the signal of each period may be a vertex to two bottoms of the signal of the period The magnitude of each bottom point in the point.

Specifically, the wearable device can acquire a physiological signal every 3 s to obtain a waveform of a physiological signal. The wearable device can record the period value of the signal of the ith cycle as T _i . The wearable device can obtain the period value of the signal of each period according to the number of points included in the signal of each period in the physiological signal and the time interval between the two points, such as the period value T _i of the signal of the ith period. For example, in the case where the sampling frequency is 100 Hz, the time interval between every two discretes in the physiological signal waveform shown in FIG. 5 may be 0.01 s. At this time, the waveform of the signal of the first period shown in FIG. 5 may include 30 points, and the period value T ₁ of the signal of the first period may be 0.3 s.

The wearable device may determine the current preset threshold range according to the signal of the period before the signal of the ith period. Specifically, the wearable device may obtain an initial preset threshold range according to an average value of characteristic values of signals of all periods in a set of physiological signals acquired for the first time. Then, the wearable device may update the initial preset threshold range according to the feature values of the physiological signals of all the cycles acquired subsequently to obtain the current preset period value range. Illustrative, the mean of the current period value

The current preset period value range may be

Similarly, the average value of the current left branch height value of the physiological signal acquired by the wearable device can be recorded as

The mean value of the current right branch height value can be written as

The current preset left height value range of the physiological signal acquired by the wearable device may be

The current preset left branch height value range can be

It should be noted that, in the embodiment of the present invention, the preset threshold range obtained by the wearable device according to the average value of the acquired feature values of the physiological signals is not unique, and may be adjusted by the relevant technical personnel according to actual conditions.

S1202: The wearable device determines that the feature value of the signal of the i-th cycle is not within the current preset threshold, and determines that the signal of the i-th cycle is an abnormal physiological signal.

Specifically, the eigenvalue of the signal of the ith period is not in the current preset threshold range, and includes: the period value of the signal of the ith period is not in the current preset period range, and/or the height of the signal of the ith period The value is not within the current preset height range. For example, the value range of the period value T _i of the signal of the i-th period is not at

At the time, the signal of the i-th cycle is an abnormal physiological signal.

Correspondingly, before determining the signal quality of the signal of the i-th cycle according to the similarity between the signal of the i-th cycle and the current set of signal templates, the wearable device may determine the i-th of the feature value of the signal of the i-th cycle. The signal of one cycle may be a normal physiological signal. Specifically, the foregoing method may further include S1203 before S304:

S1203. The wearable device determines that the feature value of the signal of the ith cycle is within a current preset threshold range.

The above steps 1201-1203 can all be performed by the processing component 102 in the wearable device 10 shown in FIG. 1.

Specifically, the eigenvalue of the signal of the ith period is in the current preset threshold range, and the period value of the signal of the ith period is in the current preset period range and the height value of the signal in the ith period is at the current preset. Height range. For example, the period value T _i of the signal of the _ith cycle is

The left branch height value of the signal in the inner and the ith cycle is

Inside, and the right branch height of the signal of the ith cycle is

Within, the signal of the ith cycle may be a normal physiological signal.

It should be noted that, in the physiological signal quality judging method provided by the embodiment of the present invention, the wearable device can determine each week in the physiological signal according to the period value and the height value in the characteristic value of the physiological signal. The signal quality of the signal. The feature point of the physiological signal can be judged by the wearable device to extract the characteristic point of the physiological signal, and the calculation amount in the process of judging the physiological signal quality can be reduced to some extent.

Further, the wearable device can determine the current preset threshold range according to the physiological signal before the signal of the i-th cycle. Specifically, the wearable device may obtain an initial preset threshold range according to an average value of characteristic values of signals of all periods in a set of physiological signals acquired for the first time. Then, the wearable device may update the initial preset threshold range according to the feature value of the signals of all the cycles in the subsequently acquired physiological signal to obtain the current preset threshold range. Therefore, in another possible implementation manner, the method provided by the embodiment of the present invention may further include S1301 and S1302 after S303. Illustratively, as shown in FIG. 13 , it is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. S1301 and S1302 may also be included after S303 in FIG. 13:

S1301: The wearable device determines a current preset threshold range according to the physiological signal before the signal of the i-th cycle.

The wearable device may determine the current preset threshold range according to the signal of the period before the signal of the ith period. Specifically, the wearable device may obtain an initial preset period value range according to an average value of period values of signals of all periods in a set of physiological signals acquired for the first time. Exemplarily, the wearable device can obtain an initial preset period value range according to an average value of period values of signals of all periods in the physiological signal acquired in the first 3 seconds. Then, the wearable device may update the initial preset period value range according to the period value of the physiological signal acquired every 3 s time interval before the signal of the ith period of the ith period to obtain the current preset period value range.

Similarly, the wearable device can obtain an initial preset left support height value range and an initial preset left support height value range according to the mean value of the height values of the signals of all the cycles in the first set of physiological signals acquired. Then, the wearable device may update the preset left support height value range and the initial preset left support height value range according to the height value of the subsequently acquired physiological signal to obtain the current preset left support height value range and the current preset left support height range. Range of values.

Exemplarily, the wearable device can obtain an initial preset left-branch range and an initial right-branch height range according to the mean value of the height values of the signals of all the periods in the physiological signal acquired in the first 3 seconds. Subsequently, the wearable device may update the initial preset left-branch value range and the initial right-branch height value range according to the height values of the signals of all the periods in the physiological signals acquired every 3 s intervals before the signal of the subsequent i-th cycle. The range of the preset preset value range is obtained by the current preset left branch value range and the current preset right branch height value range.

It should be noted that the wearable device may update the current preset period value range according to the period value of all periods of the physiological signals acquired every 3 s intervals after the signal of the i-th period to obtain a new current preset period. Range of values. Correspondingly, the foregoing method may further include S1302 after S1203:

S1302: The wearable device updates the current preset threshold range according to the feature value of the signal of the i-th cycle.

The above steps 1301-1302 can all be performed by the processing component 102 in the wearable device 10 shown in FIG. 1.

It should be noted that, in the physiological signal quality determining method provided by the embodiment of the present invention, the current preset threshold range is continuously updated according to the physiological signal acquired in real time; and the current preset threshold range is a physiological signal obtained by the wearable device according to the acquired The current preset threshold range is obtained according to the global variable; therefore, the current preset threshold range is consistent with the physiological signal acquired by the wearable device in real time. Therefore, the physiological signal quality judging method provided by the embodiment of the invention can further improve the accuracy of the physiological signal quality judgment result.

Further, after determining the signal quality of the signal of each period in the physiological signal, the wearable device may acquire the physiological information of the human body using the determined normal physiological signal. Specifically, in another possible implementation manner, after the foregoing S304 or S603 or S604, the foregoing method may further include S1401. Illustratively, as shown in FIG. 14, is a schematic flowchart of another physiological signal quality determining method according to an embodiment of the present invention. S1401 may also be included after S304 in FIG. 14:

S1401: The wearable device outputs a signal quality judgment result.

The above-described step 1401 can be performed by the processing component 102 in the wearable device 10 shown in FIG. 1 through the multimedia component 104.

The signal quality judgment result includes that the signal of the i-th cycle is a normal physiological signal or an abnormal physiological signal, and the signal of each period before the signal of the i-th cycle is a normal physiological signal or an abnormal physiological signal. Specifically, the wearable device can perform different markings for the normal physiological signal and the abnormal physiological signal, and can also output the proportion of the normal physiological signals in the signals of all the cycles in the acquired physiological signals, which is not limited by the embodiment of the present invention. . In this way, the physiological signal quality judgment result judged by the wearable device can be displayed to the user or the related technical personnel relatively intuitively, so that the user experience is better.

It should be noted that, in the method for judging the physiological signal quality provided by the embodiment of the present invention, the wearable device can judge the signal quality of the collected physiological signal in real time and on a cycle-by-cycle basis, and accurately distinguish any cycle of the physiological signal. Whether the signal is a normal physiological signal or an abnormal physiological signal. In this way, the wearable device can obtain more accurate physiological information of the human body according to the normal physiological signals obtained by the judgment.

The solution provided by the embodiment of the present invention is mainly introduced from the perspective of the wearable device in the physiological signal quality judging device. It can be understood that the physiological signal quality judging device includes a hardware structure and/or a software module corresponding to each function in order to implement the above functions. Those skilled in the art will readily appreciate that the present invention can be implemented in a combination of hardware or hardware and computer software in combination with the algorithm steps of the various examples described in the embodiments disclosed herein. Whether a function is implemented in hardware or computer software to drive hardware depends on the specific application and design constraints of the solution. A person skilled in the art can use different methods for implementing the described functions for each particular application, but such implementation should not be considered to be beyond the scope of the present invention.

The embodiment of the present invention may divide the function module by the physiological signal quality judging device according to the above method example. For example, each function module may be divided according to each function, or two or more functions may be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of the module in the embodiment of the present invention is schematic, and is only a logical function division, and the actual implementation may have another division manner.

FIG. 15 is a schematic diagram showing a possible composition of the physiological signal quality judging device provided in the above embodiment. As shown in FIG. 15, the physiological signal quality judging device 15 may be configured. The method includes an acquisition module 151, an extraction module 152, a division module 153, and a determination module 154. The acquisition module 151 is configured to support the physiological signal quality judging device 15 to execute S301 in the above embodiment, and/or other processes for the techniques described herein. The extraction module 152 is configured to support the physiological signal quality judging device 15 to perform S302 in the above embodiments, and/or other processes for the techniques described herein. The dividing module 153 is configured to support the physiological signal quality judging device 15 to execute S303 in the above embodiment, and/or other processes for the techniques described herein. The judging module 154 is configured to support the physiological signal quality judging device 15 to execute S304, S602, S603, S604, and S1202 in the above embodiments, and/or other processes for the techniques described herein.

Further, FIG. 16 shows another possible composition diagram of the physiological signal quality judging device provided in the above embodiment. As shown in FIG. 16, the physiological signal quality judging device 15 may further include: a determining module 155. The determining module 155 is configured to support the physiological signal quality judging device 15 to perform S601 and S1301 in the above embodiments, and/or other processes for the techniques described herein.

Further, FIG. 17 shows another possible composition diagram of the physiological signal quality judging device provided in the above embodiment. As shown in FIG. 17, the physiological signal quality judging device 15 may further include an updating module 156. The update module 156 is configured to support the physiological signal quality judging device 15 to perform S701, S801, S802, and S1302 in the above embodiments, and/or other processes for the techniques described herein.

Further, FIG. 18 shows another possible composition diagram of the physiological signal quality judging device provided in the above embodiment. As shown in FIG. 18, the physiological signal quality judging device 15 may further include: an obtaining module 157. The obtaining module 157 is configured to support the physiological signal quality judging device 15 to execute S901, S1001, S1002, S1102, S1102, S1201 and S1202 and S1203 in the above embodiments, and/or other processes for the techniques described herein.

Further, FIG. 19 shows another possible composition diagram of the physiological signal quality judging device provided in the above embodiment. As shown in FIG. 19, the physiological signal quality judging device 15 may further include an output module 158. The output module 158 is configured to support the physiological signal quality judging device 15 to perform S1401 in the above embodiment, and/or other processes for the techniques described herein.

It should be noted that all the related content of the steps involved in the foregoing method embodiments may be referred to the functional descriptions of the corresponding functional modules, and details are not described herein again.

The physiological signal quality judging device provided by the embodiment of the present invention is configured to perform the above physiological signal quality judging method, and thus can achieve the same effect as the above physiological signal quality judging method.

In the case of adopting an integrated unit, the above-mentioned extraction module 152, division module 153, determination module 154, determination module 155, update module 156, acquisition module 157, and the like can be integrated into one processing module. The processing module may be a processor or a controller, such as a CPU, a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), and a field programmable gate array. (Field Programmable Gate Array, FPGA) or other programmable logic device, transistor logic Pieces, hardware components, or any combination thereof. It is possible to implement or carry out the various illustrative logical blocks, modules and circuits described in connection with the present disclosure. The processing unit described above may also be a combination of computing functions, such as one or more microprocessor combinations, a combination of a DSP and a microprocessor, and the like. The storage module can be a memory. The above acquisition module 151 can be implemented by an input device. The output module 158 described above can be implemented by a display.

When the processing module is a processor and the storage module is a memory, the embodiment of the present invention provides a physiological signal quality determining apparatus 20 as shown in FIG. As shown in FIG. 20, the physiological signal quality judging device 20 includes a processor 201, a memory 222, a display 203, an inputter 204, and a bus 205. The processor 201, the memory 202, the display 203, and the inputter 204 are connected to one another via a bus 205. The bus 205 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus 205 can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in FIG. 20, but it does not mean that there is only one bus or one type of bus.

Illustratively, the input device 204 described above may include a camera and a wearable sensor or the like, such as the sensor assembly 101 in the wearable device 10. The display 203 described above may be the multimedia component 104 or the audio component 105 in the wearable device 10.

The detailed description of each module in the physiological signal quality judging device 20 provided by the embodiment of the present invention and the technical effects of each module performing the related method steps in the foregoing embodiments may refer to the related description in the method embodiment of the present invention. , will not repeat them here.

Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and brevity of the description, only the division of the above functional modules is illustrated. In practical applications, the above functions can be allocated according to needs. It is completed by different functional modules, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. For the specific working process of the system, the device and the unit described above, reference may be made to the corresponding process in the foregoing method embodiments, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be used. Combinations can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one single unit. Yuanzhong. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone computer program product, can be stored in a computer readable storage medium.

The technical solution of the present application can be implemented in whole or in part in the form of a computer program product when implemented using software. The computer program product includes at least one instruction. When the instructions are loaded and executed on a computer, the processes or functions described in accordance with embodiments of the present invention are generated in whole or in part. The computer can be a computer, a special purpose computer, a computer network, or other programmable device. The instructions may be stored in a computer readable storage medium or transferred from one computer readable storage medium to another computer readable storage medium, for example, the computer may be passed from a website site, computer, server or data center Axle cable, optical fiber, digital subscriber line (DSL) and other wired methods, or infrared, wireless, microwave, etc. wireless transmission to another website site, computer, server or data center. The computer readable medium can be any available media that can be accessed by a computer or a data storage device such as a server, data center, or the like that includes one or more available media. The usable medium may be a magnetic medium such as a floppy disk, a hard disk, or a magnetic tape, or a semiconductor medium such as a solid state disk (SSD).

The foregoing is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. . Therefore, the scope of protection of the present application should be determined by the scope of the claims.

Claims

A method for judging physiological signal quality, comprising:

Collecting a physiological signal, the physiological signal being a periodic signal or a periodic signal;

Extracting feature points of the physiological signal, the feature points including feature points for indicating the period of the physiological signal;

Dividing a period of the physiological signal according to a characteristic point of the physiological signal;

Determining, according to the similarity between the signal of the ith period and the current set of signal templates, the signal quality of the signal of the ith period; wherein the signal template set includes N signal templates, and the N signal templates are based on The physiological signal before the signal of the i-th cycle is acquired, the N is greater than or equal to 2, and the i is greater than the N.
The method according to claim 1, wherein the determining the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the set of signal templates comprises:

Determining a similar result of the signal of the ith period, the similar result of the signal of the ith period is used to indicate a similarity between the signal of the ith period and the current set of signal templates;

If the similar result of the signal of the ith period satisfies a preset similar condition, determining that the signal of the ith period is a normal physiological signal, and the preset similar condition is preset;

If the similar result of the signal of the ith period does not satisfy the preset similar condition, it is determined that the signal of the ith period is an abnormal physiological signal.
The method according to claim 2, wherein in the case where it is determined that the similar result of the signal of the i-th cycle is better than the similar result of at least one of the N signal templates, the method further The method includes: updating the current signal template set according to the signal of the ith period, wherein a similar result of one of the N signal templates is obtained according to a physiological signal before the signal of the ith period.
The method according to claim 3, wherein the updating the current signal template set according to the signal of the ith period comprises:

The signal of the i-th cycle is used to replace the signal template with the worst result in the current set of signal templates.
The method according to any one of claims 1 to 4, wherein the signal of the signal of the i-th period is judged by the similarity between the signal according to the i-th period and the current set of signal templates Before the quality, the method further comprises: acquiring the current signal template set according to the physiological signal preceding the signal of the i-th cycle.
The method according to claim 4, wherein the acquiring the current signal template set according to the physiological signal preceding the signal of the ith period comprises:

Obtaining an initial signal template set according to signals of the previous N+a periods;

And acquiring the current signal template set according to the physiological signal between the initial signal template set and the signal of the N+ath period to the signal of the ith period.
The method according to claim 6, wherein the acquiring the initial signal template set according to the signal of the previous N+a periods comprises:

Determining similar results for signals in each of the previous N+a cycles of the signal; the a is greater than equal An integer of 0, the N+a being smaller than the i; wherein a similar result of a signal of one cycle of the signals of the first N+a periods is a signal of the period and the first N+a periods a signal consisting of similarities between signals of cycles other than the periodic signals;

A signal of the first N cycles of the same result of the previous N+a cycles is determined as the initial set of signal templates.
The method according to claim 7, wherein after the extracting the feature points of the physiological signal, the method further comprises:

Obtaining a feature value of the signal of the ith cycle according to a feature point of the physiological signal;

Determining that the eigenvalue of the signal of the ith period is not within the current preset threshold, and determining that the signal of the ith period is an abnormal physiological signal, and the current preset threshold range is according to the ith period The physiological signal before the signal is determined;

Before determining the signal quality of the signal of the ith period according to the similarity between the signal of the ith period and the set of signal templates, the method further includes: determining characteristics of the signal of the ith period The value is in the current preset threshold range.
The method according to claim 8, wherein the characteristic value of the signal of the ith period comprises: a period value of the signal of the ith period and/or a height value of a signal of the ith period ;

The current preset threshold range includes: a current preset period range and/or a current preset height range; the feature value of the signal of the ith period is not in the current preset threshold range, and includes: the ith The period value of the signal of the period is not in the current preset period range, and/or the height value of the signal of the ith period is not in the current preset height range;

The characteristic value of the signal of the ith period is in the current preset threshold range, including: the period value of the signal of the ith period is in the current preset period range, and the ith period The height value of the signal is in the current preset height range.
The method according to claim 9, wherein before the acquiring the feature value of the signal of the ith period according to the feature point of the physiological signal, the method further comprises:

Determining, according to a signal of a period before the signal of the ith period, the current preset threshold range;

After the acquiring the feature value of the signal of the ith period according to the feature point of the physiological signal, the method further includes:

And updating the current preset threshold range according to the feature value of the signal of the ith period.
The method of any of claims 1 to 10, further comprising:

Outputting a signal quality judgment result, wherein the signal quality judgment result includes that the signal of the i-th cycle is a normal physiological signal or the signal of the i-th cycle is an abnormal physiological signal, and before the signal of the i-th cycle The signal of each cycle is a normal physiological signal or the signal of each cycle is an abnormal physiological signal;

Wherein, if the similar result of the signal of the one cycle before the signal of the i-th cycle satisfies the preset similar condition, the signal of the cycle is a normal physiological signal; if the signal of the i-th cycle is before the signal If the similar result of the signal of one cycle does not satisfy the preset similar condition, the signal of the cycle is an abnormal physiological signal.
A physiological signal quality judging device, comprising:

An acquisition module, configured to collect a physiological signal, wherein the physiological signal is a periodic signal or a periodic signal;

An extraction module, configured to extract a feature point of the physiological signal collected by the collected module, where the feature point includes a feature point for indicating the period of the physiological signal;

a dividing module, configured to divide a period of the physiological signal according to a feature point of the physiological signal extracted by the extracting module;

a determining module, configured to determine, according to the similarity between the signal of the ith period and the current set of signal templates, a signal quality of the signal of the ith period; wherein the signal template set includes N signal templates, The N signal templates are acquired according to the physiological signal before the signal of the ith period collected by the acquisition module, the N is greater than or equal to 2, and the i is greater than the N.
The device according to claim 12, further comprising:

a determining module, configured to determine a similar result of the signal of the ith period divided by the dividing module, where a similar result of the signal of the ith period is used to indicate the signal of the ith period and the current signal Similarity between template collections;

The determining module is configured to: if the similar result of the signal of the ith period satisfies a preset similar condition, determine that the signal of the ith period is a normal physiological signal, and the preset similar condition is preset If the similar result of the signal of the ith period does not satisfy the preset similar condition, it is determined that the signal of the ith period is an abnormal physiological signal.
The apparatus according to claim 13, further comprising: an updating module, configured to determine a similar result of the signal of the i-th cycle is better than a similar result of at least one of the N signal templates And the current signal template set is updated according to the signal of the ith period, wherein the similarity of one of the N signal templates is obtained according to a physiological signal before the signal of the ith period.
The apparatus according to claim 14, wherein the updating module is specifically configured to replace the signal template with the lowest similarity in the current signal template set by using the signal of the ith period.
The device according to any one of claims 12-15, further comprising:

And an acquiring module, configured to: according to the similarity between the signal of the ith period and the current signal template set, determine the signal quality of the signal of the ith period, according to the signal of the ith period The previous physiological signal acquires the current set of signal templates.
The apparatus according to claim 16, wherein the acquiring module is configured to acquire an initial signal template set according to the signals of the first N+a periods; according to the initial signal template set and the N+a period The physiological signal between the signals of the ith cycle of the signal acquires the current set of signal templates.
The apparatus according to claim 17, wherein the determining module is further configured to determine a similar result of a signal of each of the first N+a periods of signals; the a is an integer greater than or equal to 0, The N+a is smaller than the i; wherein a similar result of the signal of one cycle of the signals of the first N+a periods is a signal of the period and a signal of the previous N+a period Composed of similarities between signals of other periods than the periodic signals;

The obtaining module is specifically configured to use the first N+a period of the letter determined by the determining module The signals of the first N periods with the best results in the number are determined as the initial set of signal templates.
The device according to claim 18, wherein the obtaining module is further configured to: after the extracting module extracts a feature point of the physiological signal, acquire the ith according to a feature point of the physiological signal Characteristic value of a signal of a period;

The determining module is further configured to determine that the eigenvalue of the signal of the ith period is not within the current preset threshold, and determine that the signal of the ith period is an abnormal physiological signal, and the current preset threshold The range is determined according to a signal of a period before the signal of the i-th period; before the signal quality of the signal of the ith period is judged by the similarity between the signal according to the ith period and a set of signal templates, Determining that the feature value of the signal of the ith cycle is in the current preset threshold range.
The apparatus according to claim 19, wherein the characteristic value of the signal of the ith period comprises: a period value of the signal of the ith period and/or a height of a signal of the ith period The current preset threshold range includes: a current preset period range and/or a current preset height range;

The feature value of the signal of the ith period is not in the current preset threshold range, and the period value of the signal of the ith period is not in the current preset period range, and/or the The height values of the signals of the i periods are not in the current preset height range;

The characteristic value of the signal of the ith period is in the current preset threshold range, including: the period value of the signal of the ith period is in the current preset period range, and the ith period The height value of the signal is in the current preset height range.
The apparatus according to claim 20, wherein the determining module is further configured to: before the acquiring module acquires the feature value of the signal of the ith period according to the feature point of the physiological signal, according to The physiological signal preceding the signal of the i-th cycle determines the current preset threshold range;

The update module is further configured to: after the acquiring module acquires the feature value of the signal of the i-th cycle according to the feature point of the physiological signal, update the feature value of the signal according to the i-th cycle The current preset threshold range.
The device according to any one of claims 12 to 21, further comprising:

And an output module, configured to output a signal quality determination result, where the signal quality determination result includes that the signal of the i th period determined by the determining module is a normal physiological signal or the signal of the i th period is an abnormal physiological signal And the signal of each period before the signal of the i-th period is a normal physiological signal or the signal of each period is an abnormal physiological signal;

Wherein, if the similar result of the signal of one period before the signal of the ith period satisfies the preset similar condition, determining that the signal of the period is a normal physiological signal; if the signal of the ith period is before If the similar result of the signal of one cycle does not satisfy the preset similar condition, it is determined that the signal of the cycle is an abnormal physiological signal.
A physiological signal quality judging device, comprising: a processor, a memory, a display, an input device and a bus;

The memory is for storing at least one instruction, the processor, the memory, the display, and the input device are connected by the bus, and when the device is running, the processor performs the The at least one instruction stored in the memory to cause the apparatus to perform the physiological signal quality determination method according to any one of claims 1-11.
A computer storage medium, comprising: at least one instruction;

The computer is caused to perform the physiological signal quality judging method according to any one of claims 1 to 11 when the at least one instruction is run on a computer.
A computer program product, comprising: at least one instruction;

The computer is caused to perform the physiological signal quality judging method according to any one of claims 1 to 11 when the at least one instruction is run on a computer.